Distributed controller clustering in software defined networks
Software Defined Networking (SDN) is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs) brings novel challenges of reliability, scalability, fault tolerance and i...
| Hlavní autoři: | , , , , , , , |
|---|---|
| Médium: | Článek |
| Vydáno: |
Public Library of Science
2017
|
| Témata: |
| _version_ | 1825721264092741632 |
|---|---|
| author | Abdelaziz, Ahmed Ang, Tan Fong Gani, Abdullah Garba, Usman Khan, Suleman Akhunzada, Adnan Talebian, Hamid Choo, Kim-Kwang Raymond |
| author_facet | Abdelaziz, Ahmed Ang, Tan Fong Gani, Abdullah Garba, Usman Khan, Suleman Akhunzada, Adnan Talebian, Hamid Choo, Kim-Kwang Raymond |
| author_sort | Abdelaziz, Ahmed |
| collection | UM |
| description | Software Defined Networking (SDN) is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs) brings novel challenges of reliability, scalability, fault tolerance and interoperability. In this paper, we proposed a novel clustered distributed controller architecture in the real setting of SDNs. The distributed cluster implementation comprises of multiple popular SDN controllers. The proposed mechanism is evaluated using a real world network topology running on top of an emulated SDN environment. The result shows that the proposed distributed controller clustering mechanism is able to significantly reduce the average latency from 8.1% to 1.6%, the packet loss from 5.22% to 4.15%, compared to distributed controller without clustering running on HP Virtual Application Network (VAN) SDN and Open Network Operating System (ONOS) controllers respectively. Moreover, proposed method also shows reasonable CPU utilization results. Furthermore, the proposed mechanism makes possible to handle unexpected load fluctuations while maintaining a continuous network operation, even when there is a controller failure. The paper is a potential contribution stepping towards addressing the issues of reliability, scalability, fault tolerance, and inter-operability. |
| first_indexed | 2024-03-06T05:47:44Z |
| format | Article |
| id | um.eprints-19255 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:47:44Z |
| publishDate | 2017 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | um.eprints-192552018-10-12T02:32:14Z http://eprints.um.edu.my/19255/ Distributed controller clustering in software defined networks Abdelaziz, Ahmed Ang, Tan Fong Gani, Abdullah Garba, Usman Khan, Suleman Akhunzada, Adnan Talebian, Hamid Choo, Kim-Kwang Raymond QA75 Electronic computers. Computer science Software Defined Networking (SDN) is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs) brings novel challenges of reliability, scalability, fault tolerance and interoperability. In this paper, we proposed a novel clustered distributed controller architecture in the real setting of SDNs. The distributed cluster implementation comprises of multiple popular SDN controllers. The proposed mechanism is evaluated using a real world network topology running on top of an emulated SDN environment. The result shows that the proposed distributed controller clustering mechanism is able to significantly reduce the average latency from 8.1% to 1.6%, the packet loss from 5.22% to 4.15%, compared to distributed controller without clustering running on HP Virtual Application Network (VAN) SDN and Open Network Operating System (ONOS) controllers respectively. Moreover, proposed method also shows reasonable CPU utilization results. Furthermore, the proposed mechanism makes possible to handle unexpected load fluctuations while maintaining a continuous network operation, even when there is a controller failure. The paper is a potential contribution stepping towards addressing the issues of reliability, scalability, fault tolerance, and inter-operability. Public Library of Science 2017 Article PeerReviewed Abdelaziz, Ahmed and Ang, Tan Fong and Gani, Abdullah and Garba, Usman and Khan, Suleman and Akhunzada, Adnan and Talebian, Hamid and Choo, Kim-Kwang Raymond (2017) Distributed controller clustering in software defined networks. PLoS ONE, 12 (4). e0174715. ISSN 1932-6203, DOI https://doi.org/10.1371/journal.pone.0174715 <https://doi.org/10.1371/journal.pone.0174715>. http://dx.doi.org/10.1371/journal.pone.0174715 doi:10.1371/journal.pone.0174715 |
| spellingShingle | QA75 Electronic computers. Computer science Abdelaziz, Ahmed Ang, Tan Fong Gani, Abdullah Garba, Usman Khan, Suleman Akhunzada, Adnan Talebian, Hamid Choo, Kim-Kwang Raymond Distributed controller clustering in software defined networks |
| title | Distributed controller clustering in software defined networks |
| title_full | Distributed controller clustering in software defined networks |
| title_fullStr | Distributed controller clustering in software defined networks |
| title_full_unstemmed | Distributed controller clustering in software defined networks |
| title_short | Distributed controller clustering in software defined networks |
| title_sort | distributed controller clustering in software defined networks |
| topic | QA75 Electronic computers. Computer science |
| work_keys_str_mv | AT abdelazizahmed distributedcontrollerclusteringinsoftwaredefinednetworks AT angtanfong distributedcontrollerclusteringinsoftwaredefinednetworks AT ganiabdullah distributedcontrollerclusteringinsoftwaredefinednetworks AT garbausman distributedcontrollerclusteringinsoftwaredefinednetworks AT khansuleman distributedcontrollerclusteringinsoftwaredefinednetworks AT akhunzadaadnan distributedcontrollerclusteringinsoftwaredefinednetworks AT talebianhamid distributedcontrollerclusteringinsoftwaredefinednetworks AT chookimkwangraymond distributedcontrollerclusteringinsoftwaredefinednetworks |